The volume of data generated globally is growing exponentially every second, reflecting the impact of the digital transformation on our lives. According to Statista, more than 402.74 million terabytes are produced every day, and this figure continues to rise. With 5.45 billion people connected to the Internet by July 2024, as well as 18.8 billion interconnected devices, the demand for high-performance networks and AI has never been more critical. These networks, which support the transfer of this data between devices, servers and data centers, need to continually evolve to keep up with this torrent of information. These networks play a crucial role, but face growing challenges, especially in sectors such as cybersecurity and artificial intelligence (AI). Although AI is advancing rapidly and impacting various segments, it still can’t fully deal with some technical and security challenges. Latency and traffic volume are problems that directly affect the performance of networks and their ability to respond to threats in real time.
Billionths that make a difference
The latency of a network may seem trivial, but in today’s digital world, fractions of a second are essential to ensure the efficiency of applications. In high-performance networks, we reduce latency as much as possible, which we measure in nanoseconds in parts of the network, such as traffic between switch chips. However, servers are responsible for around 95% of latency, as they process data before transmitting it. This creates a bottleneck that engineering teams are constantly trying to minimize. What’s more, expectations of increased bandwidth are significant. Today, networks travel at speeds of 400 gbps, but projections indicate that they will need to support 800 to 1,600 gbps in the near future. But more than raw speed, the real challenge lies in the ability to process data packets efficiently, ensuring that bandwidth is not wasted on inefficient processes.
How is RDMA driving high-performance networks?
One of the most promising solutions for improving network performance is RDMA (Remote Direct Memory Access), a technique that allows two networked devices to exchange data directly in memory, without the intervention of the processor or operating system. This results in lower latency and greater efficiency, as it eliminates the need for multiple copies of data or buffering. With this technology, high-performance networks are able to drastically reduce packet processing time, optimizing information traffic in increasingly demanding infrastructures. This type of evolution is crucial to meeting the demands that AI places on networks. Generative AI models and deep learning, for example, move huge volumes of data within data centers. Requiring networks with minimal latency and high bandwidth. Technologies such as Ethernet, InfiniBand and optical interconnections are being improved to support this massive flow of data, but the scalability of these solutions still faces limitations, especially in environments where security is a constant concern.
The impact of AI on cybersecurity
Although AI is reshaping many sectors, it still faces complex challenges in the field of cybersecurity. The massive movement of data and the need for real-time decision-making put immense pressure on networks. And AI solutions are not always enough to deal with all the threats. AI-based tools can detect patterns and respond to attacks quickly, but there are still significant limitations when it comes to mitigating sophisticated attacks, such as advanced persistent threats (APTs) and zero-day attacks. In addition, the hype surrounding AI has led to unrealistic expectations in certain sectors. Technologies such as AI-based network assistants, digital twins and autonomous networks are promising. But they are not yet fully mature to meet all the challenges of cybersecurity. In this sense, the role of human experts remains indispensable for analyzing, interpreting and reacting to complex cyber threats. AI and high-performance networks are intertwined, forming the basis of the digital revolution we are experiencing. However, even with all the potential of these technologies, they are still evolving and face significant challenges. Especially when it comes to digital security. The future will bring faster and more efficient networks, but for this to happen safely, it will be necessary to continue investing in innovation, technological improvement and integration between AI and cybersecurity solutions. Stay on top of the latest trends in cybersecurity! Subscribe to our newsletter and receive exclusive content on innovation, AI and high-performance networks.
